Takeoff and Performance Tradeoffs of Retrofit Distributed Electric

Brigham Young University BYU ScholarsArchive Faculty Publications 2019-8 Takeoff nda Performance Tradeoffs of Retrofit Distributed Electric Propulsion for Urban Transport Kevin Moore Brigham Young University, [email protected] Andrew Ning Brigham Young University, [email protected] Follow this and additional works at: https://scholarsarchive.byu.edu/facpub Part of the Mechanical Engineering Commons Original Publication Citation Moore, K., and Ning, A., “Takeoff nda Performance Tradeoffs of Retrofit Distributed Electric Propulsion for Urban Transport,” Journal of Aircraft, Aug. 2019. doi:10.2514/1.C035321 BYU ScholarsArchive Citation Moore, Kevin and Ning, Andrew, "Takeoff nda Performance Tradeoffs of Retrofit Distributed Electric Propulsion for Urban Transport" (2019). Faculty Publications. 3248. https://scholarsarchive.byu.edu/facpub/3248 This Peer-Reviewed Article is brought to you for free and open access by BYU ScholarsArchive. It has been accepted for inclusion in Faculty Publications by an authorized administrator of BYU ScholarsArchive. For more information, please contact [email protected], [email protected]. Takeoff and Performance Tradeoffs of Retrofit Distributed Electric Propulsion for Urban Transport Kevin R. Moore∗ and Andrew Ning† Brigham Young University, Provo, UT, 84602, USA While vertical takeoff and landing aircraft have shown promise for urban air transport, distributed electric propulsion on existing aircraft may offer immediately implementable alter- natives. Distributed electric propulsion could potentially decrease takeoff distances enough to enable thousands of potential inter-city runways. This conceptual study explores the effects of a retrofit of open-bladed electric propulsion units. To model and explore the design space we use blade element momentum method, vortex lattice method, linear-beam finite element analysis, classical laminate theory, composite failure, empirically-based blade noise modeling, motor and motor-controller mass models, and gradient-based optimization. With liftoff time of seconds and the safe total field length for this aircraft type undefined, we focused on the minimum conceptual takeoff distance. We found that 16 propellers could reduce the takeoff distance by over 50% compared to the optimal 2 propeller case. This resulted in a conceptual minimum takeoff distance of 20.5 meters to clear a 50 ft (15.24 m) obstacle. We also found that when decreasing the allowable noise by approximately 10 dBa, the 8 propeller case performed the best with a 43% reduction in takeoff distance compared to the optimal 2 propeller case. This resulted in a noise-restricted conceptual minimum takeoff distance of 95 meters. I. Introduction In early aircraft designs, distributed propulsion was used more out of necessity than deliberate choice. Designs such as the Dornier Do X in 1929, the Hughes H-4 Hercules in 1947, and many other large aircraft before the jet age, were constrained by the available propulsion units of the time [1]. With the dawn of the jet age, aircraft began to use fewer but larger engines. However, some distributed and blended wing jet concepts were explored as early as 1954 [2]. During the push for high altitude long endurance (HALE) aircraft design, distributed electric propulsion (DEP) emerged as a viable option with NASA’s Pathfinder in 1983 [3]. In 1988, NASA produced several concepts including distributed propulsion with the intention of lift augmentation [4], which evolved until the Helios’ destruction in 2003 [5]. In the 2000s, a third wave of aeronautics began to emerge, termed by NASA as on demand mobility (ODM) [6], or unscheduled aircraft services. Within ODM, two applications have begun to be targeted: thin-haul commuters and urban air taxis [7]. Fig. 1 NASA X-57 thin-haul concept aircraft illustration∗ showing the mid span DEP propellers in the folded cruise position. ∗Masters Student, Department of Mechanical Engineering, AIAA Student Member †Assistant Professor, Department of Mechanical Engineering, AIAA Senior Member ∗Image reprinted from “NASA Electric Research Plane Gets X Number, New Name", by A. Beutel, 2017, Retrieved from https://www.nasa.gov/press-release/nasa-electric-research-plane-gets-x-number-new-name. Public Domain Credit: NASA 1 Thin-haul commuters, the first ODM application, are aircraft designed to fly routes not justifiable by large airlines. An example concept emerged in 2014 when NASA partnered with Joby Aviation and Empirical Systems Aerospace to use the Leading Edge Asynchronous Propeller Technology (LEAPTech) as a test bed for distributed propulsion research [8]. Additionally, in 2016, NASA announced the X-57 Maxwell short haul commuter (see fig. 1) with goals to reduce the energy required for cruise by 4.8x without sacrificing cruise speed or takeoff distance [9]. Since the X-57, there has been a significant increase in the amount of research regarding DEP for thin-haul commuters in areas such as economics[10], multidisciplinary modeling requirements [11], wing aerodynamic analysis [8, 9, 12], motor design [13], avionics [14], hybrid propulsion [15], trajectory thermal considerations [16], certification and landing safety [17] and large scale multidisciplinary optimization of design and trajectory [7]. Urban air taxis, the second ODM application, are aircraft designed for 2-6 passengers and distances less than 100 miles [18]. Though there is significant infrastructure required to adopt this type of transportation, there is potential for competitive operating costs [19]. The economic possibilities have driven the development of a variety of concepts including tilt rotor, multi-rotor, and tilting ducted fans. The concept of urban air transport with conventional small fixed-wing aircraft as opposed to vertical takeoff and landing aircraft has been previously explored [20]. However, the concept of using distributed electric propulsion to shorten the runway distance is relatively recent. In the predecessor to this work [21], we used a propeller-on-wing aerodynamic model and electric component performance modeling to show an 80% reduction in takeoff rolling distance using an optimal distributed electric propulsion design as opposed to an optimal two-propeller electric configuration. More recently, Courtin et al. [22] conducted a feasibility analysis of the STOL concept for urban air transport with the geometric programming (GP) method. They took a broad approach to the STOL urban air transport problem including takeoff rolling distance, landing distance, wing spar sizing using root bending moment, propulsion effects via 2D jets, and lift augmentation using a momentum balance. According to the study, runway lengths need only be less than 150 m (500 ft) to have feasible DEP aircraft access to thousands of potential locations in cities such as Dallas and Chicago. This work builds upon previous work with the following contributions: First, we integrate a wide range of multidisciplinary models and constraints including propeller aerostructural coupling, propeller noise, aircraft takeoff path dynamics, propeller on wing interactions, power conversion efficiency, and electrical component mass. Second, we include model modifications that allow for efficient gradient based optimization using a new method for smooth gradients with respect to propeller on wing interactions. Third, we present several case studies looking at the sensitivity to a few critical parameters that help better understand the design tradeoffs of a short takeoff fixed wing aircraft in urban transport applications. II. Model Description In this section, models relating to propeller and wing aerodynamics, propeller noise, propeller aerostructural, and electrical component modeling are outlined. These include blade element momentum theory, airfoil preprocessing, BPM (Brooks, Pope, and Marcolini) noise modeling, composite structures, vortex lattice method, propeller on wing interaction modeling, electric motor performance and mass, motor controller mass, and battery mass. Several verification and validation cases are also presented. A. Propeller Aerodynamics We use CCBlade, an open source blade element momentum (BEM) code formulated to give guaranteed convergence and in turn allow for a continuously differentiable output [23].† It includes a non-normal inflow correction which allows us to mount the props in line with the wing and include the angle of attack (AOA) of the wing as the inflow angle to the prop. For atmospheric properties we use NASA’s 1976 Standard Atmosphere Model‡ [24]. From CCBlade we extract axial and tangential induced flow distributions to be able to compute the propeller wake influence on the wing. This BEM formulation uses 2D airfoil data to calculate the induction factors for each annular disk of the propeller including Prandtl hub and tip loss correction factors [25]. To properly model the induced wake velocity in BEM formulation, the tip loss factors must be included in the output induced velocities. Propeller wakes generally reach their far-field values within approximately one rotor radius [26]. In this conceptual design study, we model the propeller as being removed one radius or more from the wing for the far-field values to be applied on the wing. This removes the need to model slipstream contraction and the associated changes in wing †CCBlade.jl on BYU FLOW Lab GitHub https://github.com/byuflowlab/CCBlade.jl ‡BYU FLOW Lab GitHub Atmosphere.jl https://github.com/byuflowlab/Atmosphere.jl 2 angle of attack and spanwise flow that would otherwise be present with a propeller closer than one radius

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